Low-rank compression preserves training-data privacy and improves adversarial robustness but weakens personal-information protection, reduces ethical behavior in zero-shot use, and harms fairness.
Learning Important Features Through Propagating Activation Differences,
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Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs
Low-rank compression preserves training-data privacy and improves adversarial robustness but weakens personal-information protection, reduces ethical behavior in zero-shot use, and harms fairness.